Role description
You will lead the development of the AI systems that power a humanoid robotics platform, with a focus on Vision-Language-Action (VLA) models and world models. Your mission will be to develop the intelligence layer that allows humanoid robots to understand their environment, reason about tasks, and generate reliable actions in real-world settings.
You will drive research and engineering efforts to improve model capabilities, accelerate training, and shorten the path from AI development to real-world robot deployment. You will investigate new approaches in embodied AI, multimodal learning, simulation-driven training, and scalable data generation to enable humanoid robots to perform increasingly complex tasks.
This role requires a combination of deep research expertise and practical engineering judgment. You will translate advances in AI research into systems that enhance robot capabilities, working closely with robotics engineers to integrate models into the full humanoid robot stack for real-world applications such as factories and warehouses.
This position is in an early-stage startup environment. You will have significant ownership and autonomy, so you should be a self-starter who can operate independently, define technical direction, make key architectural decisions, and navigate ambiguity without relying on detailed guidance.
Responsibilities
- Define and lead the AI roadmap focused on Vision-Language-Action models and world models for humanoid robotics.
- Develop and improve multimodal AI models that connect perception, language understanding, reasoning, and robot actions.
- Research and implement approaches to improve training efficiency, model performance, and deployment speed.
- Develop strategies for data collection, synthetic data generation, simulation, and large-scale model training.
- Design evaluation frameworks to measure model performance, generalization, and real-world robot capabilities.
- Adapt and deploy state-of-the-art AI research into practical humanoid robot applications.
- Collaborate with robotics engineers to integrate AI models with robot control and execution systems.
- Build and lead the AI team as the company grows.
Main requirements
- PhD in machine learning, artificial intelligence, robotics, computer vision, or a related field.
- 2+ years of industry experience developing Vision-Language-Action models, world models, embodied AI systems, or related multimodal AI technologies.
- Strong understanding of multimodal learning, foundation models, and modern deep learning architectures.
- Hands-on experience training, fine-tuning, and scaling large neural networks.
- Strong Python and PyTorch skills.
- Experience with large-scale GPU training infrastructure and distributed model training.
- Experience developing AI systems using robotics datasets, video data, or large-scale trajectory data.
Other requirements
- Experience with robotics simulation environments such as Isaac Lab, Isaac Sim, MuJoCo, or similar platforms.
- Experience applying AI models to robotics, autonomous systems, or other real-world embodied applications.
- Fluent English.
Nice to have
- Published research contributions in AI/ML, robotics, computer vision, or embodied AI, with evidence of developing novel methods or approaches.
- Experience with Vision-Language-Action models (e.g., OpenVLA, RT-2, π0, or similar approaches).
- Experience developing world models, video prediction models, or generative models for embodied AI.
- Experience leading AI research projects or technical teams.
